into play with structuring and engineering a portfolio of bets. “To create the proper balance and diversification is even more important than any particular bets,” says Dalio, “which is the opposite of how most investors operate.”
Dalio deems this critically important: engineering his data series to produce as many uncorrelated bets as possible. He is constantly analyzing the spreads between any two markets in his portfolio that may generate the highest possible alpha, or, in other words, a return series.
Dalio says if you have 15 or more good, uncorrelated bets, you will improve your return to risk ratio by a factor of five. He calls this the holy grail of investing. “If you can do this thing successfully, you will make a fortune,” he says. “You’ll get the pot of gold at the end of the rainbow.”
He sets a simple example: say an investor has 15 bets and they all have an expected return of 3 percent, with a standard deviation of 10 percent, and they’re uncorrelated. And so you have one with a 3 percent expected return and a 10 percent standard deviation. And then the investor throws into the mix a second bet that also has a 3 percent return and 10 percent standard deviation but uncorrelated, thereby reducing the overall risk by about 15 percent. If the investor does that with 15 different bets, they reduce the risk by about 80 percent. Such a portfolio would still have a 3 percent expected return. But because there are still 15 uncorrelated bets outstanding, that 3 percent expected return now has only a little over 2 percent risk. That 3 percent can now be leveraged to meet the investors’ return target with far less risk.
Dalio estimates that if the firm can make money on 60 to 65 percent of its bets in any given year, the odds are very high that the fund will meet its return targets. In 2010, as the D-process continued to unfold, about 80 percent of Dalio’s bets made money.
Bridgewater sees endless opportunities to do this because spreads are uncorrelated. In doing this, the most important rule is not to compare the correlations against each other in a quantitative sense, but according to their drivers .
“But the truth is, as you get to 15 or 20 you start to reach diminishing returns,” says Dalio. “So the issue is, ‘Do you really know what you’re doing? Can you be confident it’s good?’ I used the word good . I didn’t use excellent . Can I be confident it’s good?”
Dalio thinks the best mix of assets is an amalgam of things, and advises to derive your top alpha generators from a combination of currencies, bonds, commodities, stocks, and so on, and calibrate them properly against each other, in terms of their size. For example, Bridgewater has never had a concentrated exposure to the U.S. dollar. It has always strived for diversification beyond what’s needed for liquidity. After the position has been weighted accordingly, the goal is to create an optimal beta portfolio of positions, know how they behave, how they’re structured, and how they’re priced. Then Bridgewater does that for every single position—the firm has about 100 uncorrelated alpha streams in its alpha portfolio at any given time.
Perhaps the most important application of this portfolio engineering has nothing to do with the firm’s Pure Alpha strategy. In 1994, faced with his own portfolio management decisions, Dalio created the “All Weather portfolio”—a passive asset allocation that was designed to take full advantage of diversification. “In the mid-90s I started to accumulate some money that I wanted to use to establish a family trust, and for that trust I wanted the right asset allocation mix,” he recalls. “That’s when I created the All Weather portfolio, which now accounts for virtually all of that family trust money.”
In 2001, following the equity market crash, Britt Harris, CIO of the Verizon pension fund, would become Bridgewater’s first